@article {16113, title = {Quantifying Balance Capabilities for Optimal Mechanism Design}, journal = {IEEE Transactions on Robotics}, year = {Submitted}, abstract = {For legged systems, achieving balance and locomotion depends on the system{\textquoteright}s capability to effectively and efficiently move its Center of Mass relative to its contact point(s).\ To measure this capability, we introduce a generalization of velocity gains: dynamic ratios which quantify this motion for passive contacts.\ We incorporate this generalized gain into an objective function and apply weighted matrix norms to facilitate the parameterized design optimization of 3D mechanisms.\ We then demonstrate the proposed approach in the design of a 3D 5-link biped across several different design objectives.}, author = {DeHart, Brandon J. and Gorbet, Rob and Kulic, Dana} } @article {34209, title = {Chance-Constrained Rollover-Free Manipulation Planning With Uncertain Payload Mass}, journal = {IEEE/ASME Transactions on Mechatronics}, year = {2023}, abstract = {This article presents a chance-constrained rollover-free manipulation planning method for robotic arms under payload mass uncertainty. The corresponding motion planning problem is stated as a chance-constrained nonlinear optimal control problem (NOCP) subject to kinematics and rollover stability constraints. The latter takes the form of a chance constraint that ensures a certain probability of the robot maintaining dynamic rollover stability in the presence of payload mass uncertainty. To achieve efficient solutions to the NOCP, a novel geometric bound for the stability region is derived. The novel bound is then utilized to modify the rollover-stability constraint. To showcase its benefit, comparisons between the proposed bound of the probabilistic rollover-stability measure and the naive noise model are provided through statistical analysis. The formulation{\textquoteright}s practicality is demonstrated through experiments with a Kinova Jaco2 arm mounted on a free-to-rollover platform. Results demonstrate greater robustness of the robot{\textquoteright}s motion plan to mass uncertainty and computational efficiency of the trajectory generation.}, url = {https://doi.org/10.1109/TMECH.2023.3333793}, author = {Jiazhi Song and Antoine Petraki and Brandon J. DeHart and Inna Sharf} } @mastersthesis {17953, title = {Dynamic Balance and Gait Metrics for Robotic Bipeds}, year = {2019}, type = {PhD Thesis}, url = {https://uwspace.uwaterloo.ca/handle/10012/14766}, author = {DeHart, Brandon J.} } @conference {8847, title = {Spherical Foot Placement Estimator for Humanoid Balance Control and Recovery}, booktitle = {IEEE Int. Conf. on Robotics and Automation (ICRA)}, year = {2018}, pages = {1747 - 1754}, publisher = {IEEE}, organization = {IEEE}, abstract = {One of the main challenges of bipedal gait is to avoid falling due to unknown disturbances. Compensating for these disturbances in bipeds is often achieved by leaning or stepping. In this work, the Spherical Foot Placement Estimator (SFPE) is introduced, which uses the biped{\textquoteright}s current kinematics and dynamics to predict if a step is needed, and if so where to step, to restore balance in 3D. An example of a controller using the SFPE is shown, which augments an existing optimal controller with both leaning and stepping: SFPE-based feedback is used to generate a desired momentum for momentum-based leaning while the SFPE point is used as a control reference for stepping. The new estimator outperforms existing balance criteria by providing both recovery step location prediction and
momentum objectives with smooth dynamics.}, url = {https://ieeexplore.ieee.org/document/8460718}, author = {DeHart, Brandon J. and Gorbet, Rob and Kulic, Dana} } @conference {6191, title = {Legged Mechanism Design with Momentum Gains}, booktitle = {IEEE-RAS Int. Conf. on Humanoid Robotics (HUMANOIDS)}, year = {2017}, pages = {593-598}, abstract = {

There are two main goals for any mobile, bipedal\ system: locomotion and balance. These behaviors\ both require the biped to effectively move its center of mass (COM). In\ this work, we define an optimization framework which can be\ used to design a biped that maximizes its ability to move its\ COM, without having to define an associated controller or trajectory.\ We use angular momentum gain in our objective function, as\ a measure of how efficiently a structure can move its COM based on its physical properties. As\ a comparison, we also optimize the model using a cost of\ transport-based objective function over a set of trajectories\ and show that it provides similar results. However, the cost of\ transport calculation requires slow hybrid dynamics equations\ and hand-designed trajectories, whereas the angular momentum gain\ calculation requires only the joint space inertia matrix at each\ configuration of interest.

}, url = {http://ieeexplore.ieee.org/document/8246932/}, author = {Brandon J DeHart and Dana Kulic} } @conference {6190, title = {Quantifying Balance Capabilities using Momentum Gain}, booktitle = {IEEE-RAS Int. Conf. on Humanoid Robotics (HUMANOIDS)}, year = {2017}, pages = {561-568}, abstract = {

The ability of a legged system to balance depends\ on both the control strategy used and the system{\textquoteright}s physical\ design. To quantify a system{\textquoteright}s inherent balance capabilities, we define\ momentum gains\ for general\ 2D and 3D models. We provide two methods for calculating\ these gains, and relate both velocity and momentum gains to the\ centroidal momentum of a system, a commonly used measure of\ aggregate system behaviour. Finally, we compare velocity and\ momentum gains as criteria for the design of simple balancing\ systems using a parameterized optimization framework.

}, url = {http://ieeexplore.ieee.org/document/8246928/}, author = {Brandon J DeHart and Dana Kulic} } @conference {6136, title = {Push Recovery and Online Gait Generation for 3D Bipeds with the Foot Placement Estimator}, booktitle = {IEEE Int. Conf. on Robotics and Automation (ICRA)}, year = {2014}, pages = {1937-1942}, abstract = {

Humanoid robots have many potential applications in man-made environments, including performing hazardous tasks, assisting the elderly, and as a replacement for our aging workforce. However, generating a reliable gait for biped robots is challenging, particularly for dynamic gait and in the presence of unknown external disturbances, such as a bump from someone walking by. In this work, a 3D formulation of the Foot Placement Estimator is used with a high-level control strategy to achieve a dynamic gait capable of handling external disturbances. A key benefit of this approach is that the robot is able to respond in real time to external disturbances regardless of whether it is at rest or in motion. This strategy is implemented in simulation to control a 14-DOF lower-body humanoid robot being subjected to unknown external forces, both when at rest and while walking, and shown to generate stabilizing stepping actions.

}, url = {https://doi.org/10.1109/ICRA.2014.6907115}, author = {Brandon J DeHart and Dana Kulic} } @conference {6137, title = {Tracking Visitor\&$\#$39;s Fields of Interest in Large Scale Art Installations}, booktitle = {IEEE Int. Conf. on Systems, Man, and Cybernetics (SMC)}, year = {2013}, pages = {852-857}, abstract = {

Aurora is a large-scale kinetic art installation that reacts to human presence directly, with sensors triggering outputs, and indirectly, by modifying output behaviour rules. This paper describes a novel method for estimating visitors{\textquoteright} fields of interest, their attention to specific parts of the installation, with a future goal of using this measure as a fitness function for output behaviour modification based on genetic algorithms. Due to constraints in Aurora, distributed overhead distance sensors were used as the sensory inputs. A low resolution height graph of the space below the installation is created, and the active sensors are clustered into groups. The height graph and sensor groups are used to produce a probability map of possible visitor locations. Based on these, particle filters are created to estimate the visitors{\textquoteright} state, and by extension their fields of interest. Using this overall strategy for tracking and interest prediction, an average prediction accuracy of 92\% is found when compared to a set of simulated people moving within a simulated space.

}, url = {https://doi.org/10.1109/SMC.2013.150}, author = {Brandon J DeHart and Rob Gorbet} } @mastersthesis {17954, title = {Design and Implementation of a Framework for the Interconnection of Cellular Automata in Software and Hardware}, year = {2011}, type = {MASc Thesis}, url = {https://uwspace.uwaterloo.ca/handle/10012/6264}, author = {DeHart, Brandon J.} } @conference {6138, title = {A Study of Human Performance in Recognizing Expressive Hand Movements}, booktitle = {IEEE Int. Symp. on Robot and Human Interactive Communication (RO-MAN)}, year = {2011}, pages = {93-100}, abstract = {

This paper presents a study on human performance in recognizing affective expressions conveyed through movements of hand-like structures. One movement sequence, closing and opening the hand, was performed by a demonstrator in 3 sets of 5 repeated trials, each set intending to convey a different affective expression. Three different expressions, sadness, happiness and anger, were considered. Expressive movement animations were replicated with a human-like hand model, a stick hand model and with a model resembling a palm frond structure. The structures tested have identical kinematics but different physical appearance. The ability of a human to correctly identify the intended expressive movements performed on these different structures was tested with 66 users viewing videos of the animated structures and reporting via an online questionnaire. Results show that anger is reliably perceived by observers from animated movements on different structures, while the other emotions are easily misperceived. The physical appearance of the structure has some impact on perception performance, but was not found to be statistically significant in this study. Furthermore, analyzing the participants{\textquoteright} responses in the context of the valence-arousal model of emotion shows that the subjects were able to recognize the arousal component of the affective hand movements across all structures.

}, url = {https://doi.org/10.1109/ROMAN.2011.6005276}, author = {Ali-Akbar Samadani and Brandon J DeHart and Kirsten Robinson and Dana Kulic and Eric Kubica and Rob Gorbet} }